BACKGROUND: The sanitary emergency due to COVID-19 virus obliged people to face up several changes in their everyday life becauseWorld Health Organisation (WHO) guidelines and countries' Health Systems imposed lockdown of activities and social distancing to flatten the infection curve. One of these rapid changes involved students and professors that had to turn the traditional "in presence" classes into online courses facing several problems for educational delivery. OBJECTIVES: This work aimed to investigate the factors that affected both teaching/learning effectiveness and general human comfort and wellbeing after the sudden transition from classrooms to eLearning platforms due to COVID-19 in Italy. METHODS: A workshop, involving students and experts of Human Factors and Ergonomics, has been performed to identify aspects/factors that could influence online learning. Then, from workshop output and literature studies, a survey composed of two questionnaires (one for students and one for teachers) has been developed and spread out among Italian universities students and professors. RESULTS: 700 people answered the questionnaires. Data have been analysed and discussed to define the most important changes due to the new eLearning approach. Absence of interactions with colleagues and the necessity to use several devices were some of the aspects coming out from questionnaires. CONCLUSIONS: The study shows an overview of factors influencing both teaching/learning effectiveness and general human comfort and wellbeing. Results could be considered as a basis for future investigation and optimization about the dependencies and correlations among identified factors and the characteristics of the products/interaction/environment during eLearning courses.
By
combining load adaptive algorithms with mechanobiological algorithms,
a computational framework was developed to design and optimize the
microarchitecture of irregular load adapted scaffolds for bone tissue
engineering. Skeletonized cancellous bone-inspired lattice structures
were built including linear fibers oriented along the internal flux
of forces induced by the hypothesized boundary conditions. These structures
were then converted into solid finite element models, which were optimized
with mechanobiology-based optimization algorithms. The design variable
was the diameter of the beams included in the scaffold, while the
design objective was the maximization of the fraction of the scaffold
volume predicted to be occupied by neo-formed bony tissue. The performance
of the designed irregular scaffolds, intended as the capability to
favor the formation of bone, was compared with that of the regular
ones based on different unit cell geometries. Three different boundary
and loading conditions were hypothesized, and for all of them, it
was found that the irregular load adapted scaffolds perform better
than the regular ones. Interestingly, the numerical predictions of
the proposed framework are consistent with the results of experimental
studies reported in the literature. The proposed framework appears
to be a powerful tool that can be utilized to design high-performance
irregular load adapted scaffolds capable of bearing complex load distributions.
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